Field of the Invention
This invention relates generally to enhanced target identification in an object detection system and, more particularly, to a method for grouping object sensor measurements into targets which uses road curvature information, additional target attributes and distance compression for improved grouping accuracy, and grid-based matching using hash tables for improved computational performance.
Discussion of the Related Art
Many vehicles now include object detection systems which employ any of a number of different technologies for detecting and identifying objects in the vicinity of a host vehicle, where the objects may include other vehicles, pedestrians, fixed objects, etc. The technologies used for object detection include cameras with image processing algorithms, radar, lidar and ultrasound, among others. Data from the object detection system are typically used in one or more downstream systems in the vehicle—including collision warning systems, collision avoidance systems, and other driver alert-type systems.
Object detection systems can also be used to identify curbs, lane stripes, guard rails and median walls, and the location of these items can be used in a lane sensing system to determine lane geometry in the road ahead of the host vehicle.
Given the proliferation of object detection sensors on vehicles, and the wide variety of types of objects that are to be detected, the speed and accuracy of processing all of the object sensor data is paramount. Although some progress has been made in this area in the past, more improvements are needed to achieve the goal of efficiently translating a set of raw sensor measurements into an accurate list of vehicles and other targets in the vicinity of the host vehicle.